The probability density and autocorrelation of short-term global and beam irradiance

For individual hours, a characteristic bimodal pattern of short-term global and beam irradiance is frequently observed, with modes at high and low irradiances and with low probabilities near the hourly averages. For such hours, averaging over the hour will imply smoothing of quite significant variations within the hour. Models for the probability density distributions of short-term (5 min or less) irradiances are presented in this paper. These distributions are not unique functions of the hourly averages, but depend heavily also on the irradiance variability within the hour. This intrahour variability is found to depend on the averaging time and also on the interhour variability among three hourly averages, namely, the hour in question, the preceding and the deceding hour. The distribution differences between 5 min averages and instantaneous values are, however, negligible for most practical purposes. The lag one autocorrelation is evaluated as a function of averaging time, and a first order autoregressive model is presented. With hourly averages as the only input the probability density and autoregressive model in combination produce time series of short-term intrahour averages having realistic distributions and autocorrelation structure.     

Temporal variability in direct and global irradiance at various time scales as affected by aerosols

The aerosol optical depth (AOD) is known to be a critical input for radiation modeling purposes, and partially determines the accuracy of modeled direct normal irradiance (DNI) and global horizontal irradiance (GHI). This contribution examines to what extent time variations in AOD also determine the observed variability in DNI, particularly at the daily and longer time scales. Two measures of variability are introduced: the Aerosol Variability Index (AVI) characterizes the magnitude of the variability in AOD over specific periods, from daily to yearly, whereas the Aerosol Sensitivity Index (ASI) relates the magnitude of relative variations in irradiance to absolute variations in AOD. AOD measurements at 180 Aeronet sites over the world are used to obtain clear-sky irradiances with the REST2 radiative model, as well as determinations of ASI and AVI. Large geographic variations exist in AVI, whose largest values are found over western Sahara. The variations of ASI follow a different pattern because it decreases when AOD increases. The variability in GHI is typically 2–4 times lower than that in DNI. On a long-term basis, the normal aerosol-induced variability in DNI is less than ±5% at most sites, but some areas might experience a much larger variability, comparable to that created by large volcanic eruptions. The latest such events predate most current modeled DNI or GHI datasets, making resource assessments potentially too optimistic for bankability if based on such limited data series alone.     

Parameterization of site-specific short-term irradiance variability

This article presents a set of empirical models capable of extracting metrics quantifying the short-term variability of the solar resource based upon site/time specific satellite-derived hourly irradiance data. The model is derived from over 92,000 experimental hourly data points at twenty-four sites in the United States. The model returns four metrics characterizing intra-hourly variability, including the standard deviation of the global irradiance clear sky index, and the mean index change from one time interval to the next, as well as the maximum and standard deviation of the latter. The variability time scales addressed in this paper are 20 s, one-minute, 5 min and 15 min. The trends underlying the models are robust and show little site dependency.     

Optimizing wind farm siting to reduce power system impacts of wind variability

We introduce and solve two variants of a biobjective optimization model to reduce the negative impact of wind variability on the power system by strategically locating wind farms. The first model variant considers average changes in wind power over time; the second captures extreme fluctuations in wind power. A complementary set of wind sites is selected with the aim of minimizing both residual demand and the variability in residual demand. Because exact optimization is computationally intensive, we develop two heuristics—forward and backward greedy algorithms—to find approximate solutions. The results are compared with the exact optimization results for a well‐selected subset of the data as well as to the results from selecting sites based on average wind alone. The two models are solved using demand data and potential wind sites for the Southwest Power Pool. Though both objectives can be improved by adding more sites, for a fixed number of sites, minimizing residual demand and variability in residual demand are competing objectives. We find an approximate efficient frontier to compare trade‐offs between the two objectives. We also vary the parameter in the heuristic that controls how the two objectives are prioritized. For the case study, the backward greedy algorithm is more effective at reducing the wind power variability than the forward greedy algorithm. Furthermore, using the backward algorithm for the full dataset is more effective than solving the exact optimization on a subset of the data when the results are evaluated using the full dataset.     

Future oil production in Brazil—Estimates based on a Hubbert model

This paper forecasts oil production in Brazil, according to the Hubbert model and different probabilities for adding reserves. It analyzes why the Hubbert model might be more appropriate to the Brazilian oil industry than that of Hotelling, as it implicitly emphasizes the impacts of information and depletion on the derivative over time of the accumulated discoveries. Brazil's oil production curves indicate production peaks with a time lag of more than 15 years, depending on the certainty (degree of information) associated with the reserves. Reserves with 75% certainty peak at 3.27 Mbpd in 2020, while reserves with 50% certainty peak at 3.28 Mbpd in 2028, and with 30% certainty peak at 3.88 Mbpd in 2036. These findings show that Brazil oil industry is in a stage where the positive impacts of information on expanding reserves (mainly through discoveries) may outstrip the negative impacts of depletion. The still limited number of wells drilled by accumulated discoveries also explain this assertion. Being a characteristic of frontier areas such as Brazil, this indicates the need for ongoing exploratory efforts.     

Impact of tidal-stream arrays in relation to the natural variability of sedimentary processes

Tidal Energy Converter (TEC) arrays are expected to reduce tidal current speeds locally, thus impacting sediment processes, even when positioned above bedrock, as well as having potential impacts to nearby offshore sand banks. Furthermore, the tidal dissipation at potential TEC sites can produce high suspended sediment concentrations (turbidity maxima) which are important for biological productivity. Yet few impact assessments of potential TEC sites have looked closely at sediment dynamics beyond local scouring issues. It is therefore important to understand to what extent exploitation of the tidal energy resource will affect sedimentary processes, and the scale of this impact is here assessed in relation to natural variability. At one such site in the Irish Sea that is highly attractive for the deployment of TEC arrays, we collect measurements of sediment type and bathymetry, apply a high resolution unstructured morphodynamic model, and a spectral wave model in order to quantify natural variability due to tidal and wave conditions. We then simulate the impacts of tidal-stream energy extraction using the morphodynamic model. Our results suggest that the sedimentary impacts of ‘first generation’ TEC arrays (i.e. less than 50 MW), at this site, are within the bounds of natural variability and are, therefore, not considered detrimental to the local environment. Yet we highlight potential environmental issues and demonstrate how impact assessments at other sites could be investigated.     

A practical and economic method for estimating wind characteristics at potential wind energy conversion sites

In order to assess the economic viability of installing a wind energy conversion system (WECS) at a site; it is necessary to know the wind characteristics at that site. Since it is usually impractical to measure wind at all potential sites over a suitably long period of time, it is necessary to develop a methodology that can provide accurate estimates of wind economically at potential WECS sites from data that are already available.A physically based, three-dimensional model has been developed that incorporates the effect of underlying terrain and uses available, conventional wind information from selected nearby weather stations. This model—called COMPLEX—is essentially an objective analysis computer program that interpolates values of wind from observations at irregularly spaced stations.The required statistical wind characteristics are estimated from the synthesized hourly winds, which are obtained by using the COMPLEX model; the model is used in conjunction with a method for reducing the number of variables while still retaining most of the information of the original data set. This involves eigenvectors of the covariance matrix of the original data set.The linear characteristics of the COMPLEX model have been used to obtain solutions directly for only the few eigenvectors of the input for any arbitrary set of observations from linear combinations of those solutions. We describe here an example of the application of the method to a potential wind energy conversion site at Boone, North Carolina.     

An analytical comparison of four approaches to modelling the daily variability of solar irradiance using meteorological records

Temporal solar variability significantly affects the integration of solar power systems into the grid. It is thus essential to predict temporal solar variability, particularly given the increasing popularity of solar power generation globally. In this paper, the daily variability of solar irradiance at four sites across Australia is quantified using observed time series of global horizontal irradiance for 2003–2012. It is shown that the daily variability strongly depends on sky clearness with generally low values under a clear or overcast condition and high values under an intermittent cloudiness condition. Various statistical techniques are adopted to model the daily variability using meteorological variables selected from the ERA-Interim reanalysis as predictors. The nonlinear regression technique (i.e. random forest) is demonstrated to perform the best while the performance of the simple analog method is only slightly worse. Among the four sites, Alice Springs has the lowest daily variability index on average and Rockhampton has the highest daily variability index on average. The modelling results of the four sites produced by random forest have a correlation coefficient of above 0.7 and a median relative error around 40%. While the approach of statistical downscaling from a large spatial domain has been applied for other problems, it is shown in this study that it generally suffices to use only the predictors at a single near point for the problem of solar variability. The relative importance of the involved meteorological variables and the effects of clearness on the modelling of the daily variability are also explored.     

Assessment of spatial and temporal variability in the US solar resource from radiometric measurements and predictions from models using ground-based or satellite data

The US National Renewable Energy Laboratory (NREL) is responding to a growing demand for high-accuracy solar resource data with uncertainties significantly lower than those of existing solar resource datasets, such as the National Solar Radiation Database (NSRDB). Measurements for long-term solar resource characterizations require years to complete, which is an unacceptable timeline for the rapidly emerging needs of renewable energy applications. This contribution seeks methods of reducing the uncertainty of existing long-term solar resource datasets by incorporating lower-uncertainty site-specific ground measurements of a limited period of record. In particular, various techniques are being explored to make full use of the existing high-resolution radiation data available in the NSRDB and other sources, and extrapolate them over time using locally measured data and other supportive information. The interannual variability in global and direct radiation is studied here using long-term data at various sites. NSRDB’s modeled data for the 1998-2005 period are compared to quality-controlled measurements to assess the performance of the model, which is found to vary greatly depending on climatic condition. The reported results are encouraging for applications involving concentrators at very sunny sites. Large seasonal biases are found at some cloudy sites. Various improvements are proposed to enhance the quality of the existing model and modeled data.The measurement of solar radiation to characterize the solar climate for renewable energy and other applications is a time consuming and expensive operation. Full climate characterization may require several decades of measurements—a prospect that is not practical for an industry intent on rapid deployment of solar technologies. This study demonstrates that the consistency of the solar resource in both time and space varies widely across the United States. The mapped results here illustrate regions with high and low variability and provide readers with quick visual information to help them decide where and how long measurements should be taken for a particular application. The underlying data that form these maps are also available from NREL to provide users the opportunity for more detailed analysis.     

Variations of wind speed in time on Jeju Island,Korea

In order to clarify variability in wind energy over a long-term period of 30 years, an investigation was carried out on Jeju Island in South Korea, which has complex terrain. The selected areas for this study were Jeju, Seogwipo and Seongsan, which have wind data for 30 years from 1978 to 2007. The long-term wind data measured from automated synoptic observation system (ASOS) of meteorological observatories was analyzed in accordance with inter-annual, annual and diurnal time scales. Wind variations in various time scales were quantified by both the coefficient of variation and the range of variation. As a result, the yearly average wind speed tended to slightly decrease at the Jeju site, while the other two sites have random trends. The regional deviation for wind variations was significant on Jeju Island, which may result from its complex terrain. It was found that when wind data is measured and analyzed over a longer-term period, more reliable results can be obtained. Besides these, a statistically meaningful result will be presented in this paper.     

The search for oil in the USA An econometric approach

The USA has dominated the international oil scene both as a consumer and a producer for as long as anyone wishes to remember. That it will remain a major consumer is beyond doubt. Whether it will remain a major producer for very much longer depends on how hard the search becomes for the dwindling amount of oil that remains to be found. This paper addresses the question of what kind of forces determine the exploration and production effort that has been expended and the success rate connected with this effort. The model presented is a dynamic econometric model of the exploration and production process in the USA, specified in continuous time and estimated by way of a suitable discrete approximation over the period 1938–1982. The paper shows it is possible to explain the search for oil in the USA in terms of a combination of economic behavioural functions, lag schemes, and linking identities.     

Tidal energy leasing and tidal phasing

In addition to technical and economic constraints, tidal energy leasing is generally governed by demand for sites which contain the highest tidal streams, and does not take into account the phase relationship (i.e. the time lag) between sites. Here, the outputs of a three-dimensional tidal model are analysed to demonstrate that there is minimal phase diversity among the high tidal stream regions of the NW European shelf seas. It is therefore possible, under the current leasing system, that the electricity produced by the first generation of tidal stream arrays will similarly be in phase. Extending the analysis to lower tidal stream regions, we demonstrate that these lower energy sites offer more potential for phase diversity, with a mean phase difference of 1.25 h, compared to the phase of high energy sites, and hence more scope for supplying firm power to the electricity grid. We therefore suggest that a state-led leasing strategy, favouring the development of sites which are complementary in phase, and not simply sites which experience the highest current speeds, would encourage a sustainable tidal energy industry.     

Short-term irradiance variability: Preliminary estimation of station pair correlation as a function of distance

In this article, we report on the correlation between the irradiance variability observed at two neighboring sites as a function of their distance, and of the considered variability time scale. Correlation is the factor that determines whether the combined relative fluctuations of two solar systems add up when correlation is high, or attenuate when correlation is low.Using one-dimensional virtual networks in 24 US locations and cloud motion derived from satellites as experimental evidence, we observe station pair correlations for distances ranging from 100 m to 100 km and from variability time scales ranging from 20 s to 15 min.Within the limits of the assumptions from one-dimensional virtual networks, results show that the relationship between correlation, distance and time scale is predictable and largely independent of location and prevailing insolation conditions. Further, results indicate that the distance at which station pairs become uncorrelated is a quasi linear function of the considered time scale.     

Exploring the core factors and its dynamic effects on oil price: An application on path analysis and BVAR-TVP model

As the uncertainty of oil price increases, impacts of the influential factors on oil price vary over time. It is of great importance to explore the core factors and its time-varying influence on oil price. In view of this, based on the PATH-ANALYSIS model, this paper obtains the core factors, builds an oil price system VAR model, which uses demand, supply, price, and inventory as endogenous variables, and China's net imports as well as dollar index as exogenous variables. Then we set up a BVAR-TVP (Time varying parameter) model to analyze dynamic impacts of core factors on oil price. The results show that: (1) oil prices became more sensitive to oil supply changes, and the influence delays became shorter; (2) the impact of oil inventories on oil prices with a time lag of two quarters but has a downward trend; (3) the impact of oil consumption on oil prices with a time lag of two quarters, and this effect is increasingly greater; (4) the US dollar index is always the important factor of oil price and its control power increases gradually, and the financial crisis (occurred in 2008) further strengthens the influence of US dollar.     

THE AVAILABILITY AND VARIABILITY OF THE EUROPEAN WIND RESOURCE

The purpose of this paper is to show the differences in the availability and variability between the wind at individual sites and the wind taken over a European scale. One of the questions this paper will try to answer: ‘is there a benefit from having wind farms covering a large area’, has been asked a number of times in the discussion about the usefulness of large-scale integration of wind energy. A European wind is made up of normalized stations scattered all over Europe scaled with a factor determined from the European Wind Atlas[4].     

High-frequency irradiance fluctuations and geographic smoothing

Using six San Diego solar resource stations, clear-sky indices at 1-s resolution were computed for one site and for the average of six sites separated by less than 3 km to estimate the smoothing of aggregated power output due to geographic dispersion in a distribution feeder. Ramp rate (RR) analysis was conducted on the 1-s timeseries, including moving averages to simulate a large PV plant with energy storage. Annual maximum RRs of up to 60% per second were observed, and the largest 1-s ramp rates were enhanced over 40% by cloud reflection. However, 5% per second ramps never occurred for a simulated 10 MW power plant. Applying a wavelet transform to both the clear-sky index at one site and the average of six sites showed a strong reduction in variability at timescales shorter than 5-min, with a lesser decrease at longer timescales. Comparing these variability reductions to the Hoff and Perez (2010) model, good agreement was observed at high dispersion factors (short timescales), but our analysis shows larger reductions in variability than the model at smaller dispersion factors (long timescales).     

Transient hygrothermoelastic response in a porous cylinder subjected to ramp-type heat-moisture loading

Abstract

The classical theory of heat conduction (Fourier theory) predicts an infinite speed for thermal disturbance propagation, which is physically unrealistic. By extending the classical Fourier heat conduction and Fick’s diffusion, this article develops hyperbolic diffusion/heat conduction laws with phase lags of heat/moisture flux to simulate coupled heat-moisture diffusion-propagation behavior with the Defour and Soret effects. A porous cylinder subjected to a ramp-type heating and humidifying at the surface is studied. The Laplace transform is used to obtain a closed-form solution of the temperature, moisture, displacements and stresses in the cylinder. Numerical results are calculated via the inversion of the Laplace transform. Obtained results show that the thermal/moisture relaxation time or phase lag plays a significant role in affecting transient hygrothermoelastic field. For a non-vanishing phase lag, non-Fourier and non-Fickian effects exist and hygrothermal waves have finite propagation speeds. The influences of the phase lag of heat/moisture flux and ramp-type time parameter on the transient response of hygrothermoelastic field are presented graphically. A comparison of the numerical results based on the classical model and the present one is made. The non-Fourier heat conduction and non-Fickian diffusion can effectively avoid the shortcomings induced by the classical Fourier and Fick laws.     

Study on lag time model of fire plume under a sloped ceiling

It is known that there is a lag time for smoke plume induced by fires transporting from a fire origin to the location of interest underneath an unconfined and flat ceiling.This lag behavior of smoke plume also exists for a fire under a sloped ceiling,and is fundamental to estimate the activation time of a fire detector or other fire extinguishing system.This study focuses on the lag time of smoke plume under a sloped ceiling.Based on the weak-plume theory at early-fire phase and previous studies concerning the fire plume characteristics under a sloped ceiling,a calculation method on lag time of fire plume transporting is presented in theory.Meanwhile,two dimensionless equations predicting the lag time of fire plume for steady fire and unsteady fire are proposed respectively.Furthermore,the critical time calculation equation is also proposed to determine the applicability of quasi-steady assumption for a time-dependent fire.     

Analysis of battery backup and switching controller for a fuel-cell powered automobile

In this paper, we consider the design of a fuel-cell powered automobile that utilizes methane as a source of hydrogen to power a PEM fuel cell. It is shown that when the power demand of the motor goes up suddenly, there is a time lag for generating the necessary hydrogen. A battery backup that provides the necessary power during this time lag is analyzed via an equivalent circuit model. A logic-based switching controller that switches between the fuel cell and the backup battery is designed to meet the power demand. The efficacy of this scheme is tested via simulations on a power profile obtained from a realistic speed profile of a small automobile.     

基于DEM的分布式汇流模型及其在洪水预报中的应用

基于数字高程模型,并结合国外在河网水系提取的研究成果,归纳出提取河网水系的方法,并将其应用于实际的水系提取.建立了流域尺度的概念型分布式新安江模型,该模型在栅格单元中采用新安江模型作产流计算,根据单元的不同属性 （坡地、河道）及所推求的汇流时间场建立汇流模型.将此模型应用于淮河黄泥庄以上集水区域,对黄泥庄站的洪水过程进行了模拟研究,模拟结果符合洪水预报的规范要求.